1. D ATA C OLLECTION For IB1-ITGS By Indrani Tuesday, October 30, 2012

2. W HAT IS D ATA C OLLECTION ? Data collection is any process of preparing and collecting data, for example, as part of a process improvement or similar project. The purpose of data collection is to obtain information to keep on record, to make decisions about important issues, or to pass information on to others. Data are primarily collected to provide information regarding a specific topic. Data collection usually takes place early on in an improvement project, and is often formalized through a data collection plan which often contains the following activity. Pre collection activity — agree on goals, target data, definitions, methods Collection — data collection Present Findings — usually involves some form of sorting analysis and/or presentation. Copyright Indrani@CVSL

3. W HERE DO DATA COME FROM ? All nice and collated in a database comes from: Insurance companies (claims, medications, procedures, diagnoses, etc.) Firms (demographic data, productivity data, etc.) Institution (student name, subject, marks) Offices (Employee name, address, phone, salary) Telephone Companies (Customer name, Interest) And from many other sources Copyright Indrani@CVSL

4. W HERE DO DATA COME FROM ? Take a step back – if we’re starting from scratch, how do we collect / find data? Secondary data Primary data Copyright Indrani@CVSL

5. S ECONDARY D ATA Secondary data – data someone else has collected This is what you were looking for in your assignment. Copyright Indrani@CVSL

6. S ECONDARY D ATA – E XAMPLES OF S OURCES Health departments Vital Statistics – birth, death certificates Hospital, clinic, school, nurse records Private and foundation databases Central and State governments Surveillance data from state government programs Federal agency statistics - Census, NIH, etc. Copyright Indrani@CVSL

7. S ECONDARY D ATA – L IMITATIONS What did you find on the frustrating side as you looked for data on the state’s websites? Copyright Indrani@CVSL

8. S ECONDARY D ATA – L IMITATIONS When was it collected? For how long? May be out of date for what you want to analyze. May not have been collected long enough for detecting trends. E.g. Have new anticorruption laws impacted Russia’s government accountability ratings? Copyright Indrani@CVSL

9. S ECONDARY D ATA – L IMITATIONS Is the data set complete? There may be missing information on some observations Unless such missing information is caught and corrected for, analysis will be biased. Copyright Indrani@CVSL

10. S ECONDARY D ATA – L IMITATIONS Are there confounding problems? Sample selection bias? Source choice bias? In time series, did some observations drop out over time? Copyright Indrani@CVSL

11. S ECONDARY D ATA – L IMITATIONS Are the data consistent/reliable? Did variables drop out over time? Did variables change in definition over time? E.g. number of years of education versus highest degree obtained. Copyright Indrani@CVSL

12. S ECONDARY D ATA – L IMITATIONS Is the information exactly what you need? In some cases, may have to use “proxy variables” – variables that may approximate something you really wanted to measure. Are they reliable? Is there correlation to what you actually want to measure? E.g. gauging student interest in U.W. by their ranking on FAFSA – subject to gamesmanship. Copyright Indrani@CVSL

13. S ECONDARY D ATA – A DVANTAGES No need to reinvent the wheel. If someone has already found the data, take advantage of it. Copyright Indrani@CVSL

14. S ECONDARY D ATA – A DVANTAGES It will save you money. Even if you have to pay for access, often it is cheaper in terms of money than collecting your own data. (more on this later.) Copyright Indrani@CVSL

15. S ECONDARY D ATA – A DVANTAGES It will save you time. Primary data collection is very time consuming. (More on this later, too!) Copyright Indrani@CVSL

16. S ECONDARY D ATA – A DVANTAGES It may be very accurate. When especially a government agency has collected the data, incredible amounts of time and money went into it. It’s probably highly accurate. Copyright Indrani@CVSL

17. S ECONDARY D ATA – A DVANTAGES It has great exploratory value Exploring research questions and formulating hypothesis to test. Copyright Indrani@CVSL

18. P RIMARY D ATA Primary data – data you collect Copyright Indrani@CVSL

19. P RIMARY D ATA - E XAMPLES Surveys Focus groups Questionnaires Personal interviews Experiments and observational study Copyright Indrani@CVSL

20. 3 M ETHODS FOR C OLLECTING D ATA Mgt. 450

21. T HREE M AJOR T ECHNIQUES FOR C OLLECTING D ATA : 1. Questionnaires 2. Interviews 3. Observation Copyright Indrani@CVSL

22. U SING THESE DATA GATHERING METHODS Each method has advantages and problems. No single method can fully measure the variable important to OD Examples: Questionnaires and surveys are open to self- report biases, such as respondents’ tendency to give socially desirable answers rather than honest opinions. Observations are susceptible to observer biases, such as seeing what one wants to see rather than what is actually there. Copyright Indrani@CVSL

23. U SE MORE THAN ONE Because of the biases inherent in any data- collection method, it is best to use more than one method when collecting diagnostic data. The data from the different methods can be compared, and if consistent, it is likely the variables are being validly measured. Copyright Indrani@CVSL

24. D EMOGRAPHICS Information about the people you are gathering data from is important. Collect the specific demographics necessary. Some examples Age Gender Income level Ethnic background Status (student, teacher, visitor) Be careful not to collect demographics that are not specific to your data collection purpose. Copyright Indrani@CVSL

25. Q UESTIONNAIRES : Questionnaires are one of the most efficient ways to collect data. They contain fixed-response questions about various features of an organization. These on-line or paper-and pencil measures can be administered to large numbers of people simultaneously. They can be analyzed quickly. They can be easily be fed back to employees. Questionnaires can be standard based on common research or they can be customized to meet the specific data gathering need. Copyright Indrani@CVSL

26. Q UESTIONNAIRES ; THERE ARE DRAWBACKS ; Responses are limited to the questions asked in the instrument. They provide little opportunity to probe for additional data or ask for points of clarification. They tend to be impersonal. Often elicit response biases – tend to answer in a socially acceptable manner. Copyright Indrani@CVSL

27. I NTERVIEWS Interviews are probably the most widely used technique for collecting data in OD. They permit the interviewer to ask the respondent direct questions. Further probing and clarification is possible as the interview proceeds. This flexibility is invaluable for gaining private views and feelings about the organization and exploring new issues that emerge during the interview. Copyright Indrani@CVSL

28. I NTERVIEWS Interviews may be highly structured, resembling questionnaires, or highly unstructured, starting with general questions that allow the respondent to lead the way. Interviews are usually conducted one-to-one but can be carried out in a group. Group interviews save time and allow people to build on other’s responses. Group interviews may, however, inhibit respondent’s answers if trust is an issue. Copyright Indrani@CVSL

29. I NTERVIEWS / F OCUS G ROUPS Another unstructured group meeting conducted by a manager or a consultant. A small group of 10-15 people is selected representing a larger group of people Group discussion is started by asking general questions and group members are encouraged to discuss their answers in some depth. The richness and validity of this information will depend on the extent that trust exists. Copyright Indrani@CVSL

30. D RAWBACK TO INTERVIEWS They can consume a great deal of time if interviewers take full advantage of the opportunity to hear respondents out and change their questions accordingly. Personal biases can also distort the data. The nature of the question and the interactions between the interviewer and the respondent may discourage or encourage certain kinds of responses. It take considerable skill to gather valid data. Copyright Indrani@CVSL

31. S AMPLE I NTERVIEW Q UESTIONS 1. How do management and non-management employees interact in the office? 2. How do you know when you have done an excellent job? 3. How do non-management employees learn about organizational change? 4. If you could change one or two things about the way management and non-management personnel interact, what would you change? Copyright Indrani@CVSL

32. O BSERVATIONS Observing organizational behaviors in their functional settings is one of the most direct ways to collect data. Observation can range from complete participant observation, where the OD practitioner becomes a member of the group under study to a more detached observation using a casually observing and noting occurrences of specific kinds of behaviors. Copyright Indrani@CVSL

33. A DVANTAGES TO O BSERVATION : They are free of the biases inherent in the self- report data. They put the practitioner directly in touch with the behaviors in question. They involved real-time data, describing behavior occurring in the present rather than the past. They are adapting in that they can be modified depending on what is being observed. Copyright Indrani@CVSL

34. P ROBLEMS WITH O BSERVATION Difficulties interpreting the meaning underlying the observations. Observers must decide which people to observe; choose time periods, territory and events Failure to attend to these sampling issues can result in a biased sample of data. Copyright Indrani@CVSL

35. O BSERVATION P ROTOCOL A decision needs to be made on what to observe. Example: Observe how managers and employees interact in the office. Observe who has lunch with whom. (Do managers and non-managers eat together? Do executives have a private lunch area?) Copyright Indrani@CVSL

36. P RIMARY D ATA - L IMITATIONS Uniqueness May not be able to compare to other populations Copyright Indrani@CVSL

37. P RIMARY D ATA - L IMITATIONS Do you have the time and money for: Designing your collection instrument? Selecting your population or sample? Pretesting/piloting the instrument to work out sources of bias? Administration of the instrument? Entry/collation of data? Copyright Indrani@CVSL

38. P RIMARY D ATA - L IMITATIONS Researcher error Sample bias Other confounding factors Copyright Indrani@CVSL

39. D ATA COLLECTION CHOICE What you must ask yourself: Will the data answer my research question? Copyright Indrani@CVSL

40. D ATA COLLECTION CHOICE To answer that You much first decide what your research question is Then you need to decide what data/variables are needed to scientifically answer the question Copyright Indrani@CVSL

41. D ATA COLLECTION CHOICE If that data exist in secondary form, then use them to the extent you can, keeping in mind limitations. But if it does not, and you are able to fund primary collection, then it is the method of choice. Copyright Indrani@CVSL

42. E ND OF P ACK Thank you Copyright Indrani@CVSL